Dispatch advisor to assist in selecting operating conditions of power plant that maximizes operational revenue

ABSTRACT

A dispatch advisor to assist in selecting operating conditions of a power plant that maximizes operational revenue is described. The dispatch advisor obtains a base load map for operating the power plant to meet base load power demands. The base load map includes a primary base load operating space for attaining target plant power output and efficiency, and an expanded base load portion for attaining higher plant power output and less than optimal efficiency. Both the primary base load operating space and the expanded base load portion associate power output and efficiency values of the power plant that result from a subset of operational parameter values for operating the power plant during base load. The dispatch advisor can transform the flexible base load map into one or more visualizations describing the revenue possibilities associated with operating the power plant based on operating values and attained power output and efficiency.

CROSS REFERENCE TO RELATED APPLICATIONS

The present patent application is related to concurrently filed,co-pending, and commonly assigned U.S. patent application Ser. No.______, entitled DISPATCH ADVISOR FOR OPERATING POWER PLANT WITHFLEXIBILITY (Attorney Docket No.: 603424-US-1), the disclosure of whichis incorporated herein by reference.

BACKGROUND Technical Field

Embodiments of the invention relate generally to power plants and moreparticularly, to providing a dispatch advisor to assist in selectingoperating conditions of a power plant that maximizes operationalrevenue.

Discussion of Art

Many power plants such as combined-cycle power plants employ gasturbines as a source of power to satisfy at least part of consumers'overall electrical demand. Plant operators sometimes peak-fire their gasturbines above their base capacity during peak demand periods.Peak-firing gas turbines above their base capacity produces extra poweroutput when needed, but at the expense of faster parts-life consumption(e.g., extra factored fired hours). If gas turbines are peak-fired oftenwithin the maintenance interval (or maintenance life), the incrementalparts-life consumption may cause the maintenance interval to beshortened. As a result, maintenance schedules are pulled in and extracustomer service agreement charges may be incurred. Consideration ofthese extra maintenance costs, in terms of more frequent servicing ofthe gas turbines, can lead plant asset owners to exercise peak-fire modemore conservatively than necessary, which may result in missed revenueopportunity.

BRIEF DESCRIPTION

The following presents a simplified summary of the disclosed subjectmatter in order to provide a basic understanding of some aspects of thevarious embodiments. This summary is not an extensive overview of thevarious embodiments. It is not intended to exclusively identify keyfeatures or essential features of the claimed subject matter set forthin the Claims, nor is it intended as an aid in determining the scope ofthe claimed subject matter. Its sole purpose is to present some conceptsof the disclosure in a streamlined form as a prelude to the moredetailed description that is presented later.

Embodiments are directed to providing solutions that relate to advisingoperators of power plants utilizing gas turbines such as combined-cyclepower plants, on how to select operating conditions that maximizeoperational revenue, taking into account capacity remunerationmechanisms, instantiations of market conditions, and parts-lifeconsumption and maintenance schedule of components of the power plant.The solutions provided by the various embodiments include using adispatch advisor to obtain a flexible base load map for operating thepower plant to meet base load power demands. The flexible base load mapincludes a primary base load operating space for attaining target plantpower output and efficiency, and an expanded base load portion forattaining higher plant power output and less than optimal efficiency.Both the primary base load operating space and the expanded base loadportion associate power output and efficiency values of the power plantthat result from a subset of operational parameter values for operatingthe power plant during base load. The dispatch advisor can transform theflexible base load map into one or more visualizations describing therevenue possibilities associated with operating the power plant based onoperating values and attained power output and efficiency that isrepresented in the flexible base load map.

In one embodiment, these visualizations can include interactivevisualizations that allow plant operators to directly manipulate andexplore the representations of the data in the visualizations toascertain a selection of operating conditions that can be used tooperate the power plant in a manner that satisfies any of a number ofcombinations of power plant considerations that can include one or moreof ambient, operational, contractual, regulatory, legal, and/or economicand market conditions. To this extent, the interactive visualizationscan be utilized to select operating conditions of the power plant thatmaximize operational revenue. For example, the interactivevisualizations provided by the dispatch advisor can be used to selectoperating conditions of the power plant that maximize operationalrevenue based on instantiations of market conditions. This can includeusing the visualizations to sell power in a spot market, while allowingfor a highest possible capacity payment for capacity or powercommitments entered into over a capacity market. In another embodiment,the interactive visualizations of the dispatch advisor can be used toforecast operational scenarios, manage outages and availability. Forexample, the interactive visualizations of the dispatch advisor can beused for the process of prospectively purchasing fuel for futuregenerating periods so that fuel inventory is minimized, while notincreasing the risk of a shortfall. In another example, the interactivevisualizations of the dispatch advisor can be used in the process ofprospectively setting a service and maintenance program that determineswhen to service and/or replace various parts and components of the powerplant in a manner that minimizes downtime and availability of the powerplant.

In one embodiment, a method for assisting in selecting operatingconditions of a power plant having at least one gas turbine thatmaximizes operational revenue is provided. The method comprises:obtaining, by a system comprising at least one processor, a flexiblebase load map for operating the power plant to meet base load powerdemands, wherein the flexible base load map includes a primary base loadoperating space for attaining target plant power output and efficiency,and an expanded base load portion for attaining higher plant poweroutput and sub-optimal efficiency in relation to the primary base loadoperating space, both the primary base load operating space and theexpanded base load portion including a representation that associatespower output and efficiency values of the power plant that result from asubset of operational parameter values for operating the power plantduring base load, the operational parameters including firingtemperature of the gas turbine, a position of inlet guide vanes in thegas turbine, and fuel temperature of the fuel in the gas turbine;partitioning, by the system, the flexible base load map into a pluralityof operating segments, each operating segment including a range ofoperating values for the operational parameters and corresponding poweroutput and efficiency values that are attained while operating the powerplant at the range of operating values in the operating segment; foreach of the plurality of operating segments, determining, by the system,revenue that is generated from operating the power plant over the rangeof operating values that attain the corresponding power output andefficiency values taking into consideration at least one of a pluralityof market conditions associated with a power generation market;generating, by the system, a plurality of visualizations of the revenueassociated with each of the operating segments in the partitionedflexible base load map for each of the plurality of market conditions,wherein each visualization of the revenue determined for the pluralityof market conditions includes a visual representation of the revenueassociated with operating the power plant in each of the plurality ofoperating segments based on the respective range of operating values andpower output and efficiency values that are attained with the operatingvalues; and presenting for display, with the system, one or more of theplurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions.

In another embodiment, a system is provided. The system comprises: amemory that stores executable components; a processor, operativelycoupled to the memory, that executes the executable components. Theexecutable components comprising: a dispatch advisor system forassisting in selecting operating conditions of a power plant having atleast one gas turbine that maximizes operational revenue, the dispatchadvisor system configured to perform the method comprising: obtaining,by the processor, a flexible base load map for operating the power plantto meet base load power demands, wherein the flexible base load mapincludes a primary base load operating space for attaining target plantpower output and efficiency, and an expanded base load portion forattaining higher plant power output and sub-optimal efficiency inrelation to the primary base load operating space, both the primary baseload operating space and the expanded base load portion including arepresentation that associates power output and efficiency values of thepower plant that result from a subset of operational parameter valuesfor operating the power plant during base load, the operationalparameters including firing temperature of the gas turbine, a positionof inlet guide vanes in the gas turbine, and fuel temperature of thefuel in the gas turbine; partitioning, by the processor, the flexiblebase load map into a plurality of operating segments, each operatingsegment including a range of operating values for the operationalparameters and corresponding power output and efficiency values that areattained while operating the power plant at the range of operatingvalues in the operating segment; for each of the plurality of operatingsegments, determining, by the processor, revenue that is generated fromoperating the power plant over the range of operating values that attainthe corresponding power output and efficiency values taking intoconsideration at least one of a plurality of market conditionsassociated with a power generation market; generating, by the processor,a plurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions, wherein each visualization of therevenue determined for the plurality of market conditions includes avisual representation of the revenue associated with operating the powerplant in each of the plurality of operating segments based on therespective range of operating values and power output and efficiencyvalues that are attained with the operating values; and presenting fordisplay, with the processor, one or more of the plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions.

In yet another embodiment, a non-transitory computer-readable mediumhaving stored thereon executable instructions that, in response toexecution, cause a system comprising at least one processor to performoperations directed to generating a dispatch advisor system forassisting in selecting operating conditions of a power plant having atleast one gas turbine that maximizes operational revenue is provided.The operations comprises: obtaining a flexible base load map foroperating the power plant to meet base load power demands, wherein theflexible base load map includes a primary base load operating space forattaining target plant power output and efficiency, and an expanded baseload portion for attaining higher plant power output and sub-optimalefficiency in relation to the primary base load operating space, boththe primary base load operating space and the expanded base load portionincluding a representation that associates power output and efficiencyvalues of the power plant that result from a subset of operationalparameter values for operating the power plant during base load, theoperational parameters including firing temperature of the gas turbine,a position of inlet guide vanes in the gas turbine, and fuel temperatureof the fuel in the gas turbine; partitioning the flexible base load mapinto a plurality of operating segments, each operating segment includinga range of operating values for the operational parameters andcorresponding power output and efficiency values that are attained whileoperating the power plant at the range of operating values in theoperating segment; for each of the plurality of operating segments,determining revenue that is generated from operating the power plantover the range of operating values that attain the corresponding poweroutput and efficiency values taking into consideration at least one of aplurality of market conditions associated with a power generationmarket; generating a plurality of visualizations of the revenueassociated with each of the operating segments in the partitionedflexible base load map for each of the plurality of market conditions,wherein each visualization of the revenue determined for the pluralityof market conditions includes a visual representation of the revenueassociated with operating the power plant in each of the plurality ofoperating segments based on the respective range of operating values andpower output and efficiency values that are attained with the operatingvalues; and presenting for display one or more of the plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions.

DRAWINGS

The present invention will be better understood from reading thefollowing description of non-limiting embodiments, with reference to theattached drawings, wherein below:

FIG. 1 is a block diagram of an example of a power plant in whichembodiments of the present invention are suitable for use in providingguidance on how to manage its operation in a manner that maximizesoperational revenue in accordance with an embodiment of the presentinvention;

FIG. 2 is a block diagram of an example of a dispatch advisor system foroperating a power plant having at least one gas turbine with flexibilityin accordance with an embodiment of the present invention;

FIG. 3 is a block diagram illustrating example data inputs and outputsfor the flexible base load generation component of the dispatch advisorsystem depicted in FIG. 2 in accordance with an embodiment of thepresent invention;

FIG. 4 is flow chart describing examples of operations of an algorithmassociated with the flexible base load generation component that cangenerate a flexible base load map in accordance with an embodiment ofthe present invention;

FIG. 5 is an example of a representation of a flexible base load map foroperating a power plant that can be generated by the flexible base loadgeneration component using the operations depicted in FIG. 4 inaccordance with an embodiment of the present invention;

FIG. 6 is a block diagram illustrating example data inputs and outputsfor the operational revenue optimizing component of the dispatch advisorsystem depicted in FIG. 2 in accordance with an embodiment of thepresent invention;

FIG. 7 is flow chart describing examples of operations of an algorithmassociated with the operational revenue optimizing component inaccordance with an embodiment of the present invention;

FIG. 8 is a block diagram illustrating example data inputs and outputsfor the optimized revenue/flexible base load map visualization componentof the dispatch advisor system depicted in FIG. 2 in accordance with anembodiment of the present invention;

FIG. 9 is flow chart describing examples of operations of an algorithmassociated with the optimized revenue/flexible base load mapvisualization component in accordance with an embodiment of the presentinvention;

FIG. 10 is an example showing a visualization of an optimized revenuemap within a flexible base load map in accordance with an embodiment ofthe present invention;

FIG. 11 is a block diagram illustrating example data inputs and outputsfor the service and maintenance optimizing visualization component ofthe dispatch advisor system depicted in FIG. 2 in accordance with anembodiment of the present invention;

FIG. 12 is flow chart describing examples of operations of an algorithmassociated with the service and maintenance optimizing visualizationcomponent in accordance with an embodiment of the present invention;

FIG. 13 is an example showing a visualization of optimized revenuewithin a flexible base load map for variable spot market pricing inaccordance with an embodiment of the present invention;

FIGS. 14A-14C illustrate examples how a plant operator could use thedispatch advisor system depicted in FIG. 2 to manage a power plant inaccordance with various embodiments of the present invention;

FIG. 15 is an example computing environment in which the variousembodiments may be implemented; and

FIG. 16 is an example networking environment in which the variousembodiments may be implemented.

DETAILED DESCRIPTION

Example embodiments of the present invention will be described morefully hereinafter with reference to the accompanying drawings, in whichsome, but not all embodiments are shown. Indeed, the present inventionmay be embodied in many different forms and should not be construed aslimited to the embodiments set forth herein; rather, these embodimentsare provided so that this disclosure will satisfy applicable legalrequirements. Like numbers may refer to like elements throughout.

According to aspects of the present invention, systems and methods aredisclosed which may be used to optimize the performance of powersystems, power plants, and/or thermal power generating units for a givenset of design and operating control capabilities. In exemplaryembodiments, this optimization can include guidance to an operator of apower plant in selection of optimum operating conditions of the plant.In other embodiments, this optimization can include an economicoptimization by which an operator of a power plant decides betweenalternative modes of operation in order to enhance profitability. Theseembodiments may be utilized within a particular power system in order toprovide a competitive edge in procuring advantageous economic commitmentterms during a dispatch process of the power system.

An adviser function associated with the various embodiments may guidethe operator of the power plant in the selection of optimum operatingconditions of the power plant. To this extent, the adviser function mayallow the operator to make choices between operating modes based onaccurate economic comparisons and projections. For example, the advisorfunction can assist an operator in selecting operating conditions of thepower plant that maximizes operational revenue. In one embodiment, theadvisor function can offer guidance to an operator in selectingoperating conditions of the power plant that maximizes operationalrevenue based on instantiations of market conditions. This can includeselling power in a spot market, while allowing for the highest possiblecapacity payments for capacity or power commitments entered into over acapacity market. The advisor function can also be used to assist inforecasting operational scenarios, manage outages and availability. Forexample, an operator of a power plant can use the advisor function forthe process of prospectively purchasing fuel for future generatingperiods so that fuel inventory is minimized, while not increasing therisk of a shortfall. In another example, an operator of a power plantcan use the advisor function for the process of prospectively setting aservice and maintenance program that determines when to service and/orreplace various parts and components of the power plant in a manner thatminimizes downtime and availability of the power plant.

Technical effects of some configurations of the various embodiments ofthe present invention include the generation and solution of an energysystem representation that advises or provides guidance on optimallyoperating a power plant under varying physical, operational, and/oreconomic conditions with as much flexibility as possible. In doing this,an operator of a power plant can select optimum operating conditions ofthe power plant that maximize profitability for particular power plantconsiderations. These power plant considerations can include any numberof combinations of one or more ambient, operational, contractual,regulatory, legal, and/or economic and market conditions.

Turning now to the figures, FIG. 1 shows a block diagram of an exampleof a power plant 10 in which embodiments of the present invention aresuitable for use in providing guidance on how to manage its operation inaccordance with an embodiment of the present invention. The power plant10 depicted in FIG. 1 is a combined-cycle power plant, and inparticular, is an example of 2×1 combined-cycle power plant thatcomprises two gas turbines 12 (GT 1 and GT 2) a heat recovery steamgenerator (HRSG) 14, and a steam turbine 16 (ST 1). In general, the gasturbines 12 (GT 1 and GT 2) are heated to a high temperature. The HRSG14 captures the exhaust gas from the gas turbines 12 (GT 1 and GT 2) tocreate steam that is delivered to the steam turbine 16 (ST 1). Both thegas turbines 12 (GT 1 and GT 2) and the steam turbine 16 (ST 1) candrive a generator to produce electricity that is supplied to anelectrical power grid. It is understood that this 2×1 combined-cyclepower plant configuration is only an example of one combined-cycle powerplant in which the various embodiments have utility. While the variousembodiments are described with respect to a combined-cycle power plant,these embodiments are suitable for use with other power plants thatinclude at least one gas turbine.

It is understood that the power plant 10 depicted in FIG. 1 is asimplified representation of a combined-cycle power plant, and thoseskilled in the art will appreciate that the power plant can includeother components. For example, the power plant 10 can include acomponent controller that controls various aspects of parts, components,machines, apparatuses or the like that are operatively coupled with eachof the gas turbines 12 (GT 1 and GT 2), the heat recovery steamgenerator (HRSG) 14, and the steam turbine 16 (ST 1), including, but notlimited to, sensors, valves, etc. In addition, the power plant 10 caninclude a plant controller that receives data and sends or instructs thecomponent controller to facilitate any of a number of operations. Itwill be appreciated that the component controller and the plantcontroller may be combined into a single controller. In any event, theplant controller may communicate with a plant operator and any of anumber of data resources. According to certain embodiments, the plantcontroller can issue recommendations to the plant operator regardingdesired operating setpoints for the power plant 10. The plant controllercan also receive instructions and commands from the plant operatorregarding a number of different operations. In addition, the plantcontroller may receive and store data on the operation of the componentsand subsystems of the power plant 10. The various embodiments describedherein are suitable for use as a functionality that operates as a partof the plant controller.

In a typical combined-cycle power plant, the base load of the powerplant at given ambient conditions can be defined by the firingtemperature or operating temperature of the gas turbine, and a positionof the inlet guide vanes (IGV) in the gas turbine. To this extent, thefiring temperature and the IGV position can define an operating pointfor the combined-cycle power plant with the highest output andefficiency. However, operating the combined-cycle power plant accordingto a defined operating point has its limitations.

Embodiments of the present invention overcome these limitationsassociated with operating the combined-cycle power according to anoperating point, by defining an operating space of optimum operatingconditions for operating the combined-cycle power plant that an operatorcan use as guidance to select specific settings of operationalparameters of the power plant that are represented in the operatingspace during base load at predetermined ambient conditions. Thederivation of the operating space associated with the variousembodiments is based on combined-cycle power plants that utilize gasturbines that have an option of partial peak firing. This allows anoperator to command a desired output. In some instances, this optionmakes it possible for the gas turbine to increase the firing temperature(within +35 F range) to achieve a target megawatt (MW) output. At apredetermined compressor inlet temperature (CTIM) (e.g., CTIM<22 C), theIGV position can be defined as an exhaust Mach number (the “Machnumber”). On this basis, an operating line for operating the power plantcan be defined by the firing temperature and the Mach number. Thisoperating line can be expanded from a line to an operating space thatrepresents the space of operation of the firing temperature and the Machnumber of the power plant during base load at predetermined ambientconditions. For example, in one embodiment, the operating space of thepower plant can be defined by a variable firing temperature and aconstant Mach number. From this operating space, the power plant can beoperated to achieve target output and efficiency.

The capability to operate the power plant with variable firingtemperature in order to increase output and efficiency is beneficial,however, there are drawbacks in that there is an impact on the lifecycle of parts or components of the power plant. For example, anincreased firing temperature and exposure time at the increasedtemperature will adversely impact the life cycle of combustion and hotgas path parts, which can result in maintenance and replacement costs tokeep the power plant operational for meeting base load power demands, aswell as availability issues due to service. In another scenario,increasing the Mach number can reduce the life of a rotor of the gasturbine, and thus, require maintenance. Since it is expected that as gasturbine technology evolves, the Mach numbers will increase. This willallow for more gas turbine output, and hence, more combined-cycle powerplant output, but at a lower efficiency.

In order to accommodate a larger operating space that accounts forvariable firing temperatures and Mach numbers, and the effect thatvariable operational parameters will have on the output and efficiencyof the power plant, the various embodiments are directed to improvingupon the operating space that can be based on a variable firingtemperature and a constant Mach number. For example, the variousembodiments are directed to providing an operating space that representsvariable firing temperatures and Mach numbers in relation to theireffects on the output and efficiency of the power plant. In one example,an operator of a power plant can use the operating space from thevarious embodiments that contains an expanded representation of theincreased firing temperature and Mach number values to adjust targetplant load and efficiency. To this extent, an operator can adjust thetarget plant load and efficiency to accommodate one of a number ofbusiness interests that can include, but are not limited to, maximizingrevenue, forecasting operational scenarios, managing outages andavailability, purchasing fuel, and planning for service and maintenance.

The larger operating space of the various embodiments also takes intoaccount the increased firing temperature and Mach number values that canresult in sub-optimal efficiency. As used herein, sub-optimal efficiencymeans that the power plant runs at less than full power and implies thatthe capital costs per MW of the output of the plant are higher. Inparticular, the operating space of the various embodiments is expandedto accommodate another operational parameter that can have an added rolein effecting the output and efficiency that results from the increasedfiring temperature and Mach number values. In one embodiment, thisadditional operational parameter can include the fuel temperature of thefuel in the gas turbine. With this added operational parameter in theoperational space, an operator can use the operational space to selectoptimum conditions for the firing temperature, Mach number, and the fueltemperature in those instances where it is desired to run at a higheroutput, but at sub-optimal efficiency. In this manner, the operator canadjust the firing temperature, Mach number and the fuel temperature toaccommodate one of a number of business interests that can include, butare not limited to, maximizing revenue, forecasting operationalscenarios, managing outages and availability, purchasing fuel, andplanning for service and maintenance. For example, in one embodiment,the operator can adjust these parameters to maximize operational revenuebased on instantiations of market conditions. This can include sellingpower in a spot market, while allowing for the highest possible capacitypayments for capacity or power commitments entered into over a capacitymarket. In some instances, this can be of interest to power plantoperators even despite the effect that sub-optimal efficiency can havein not yielding the highest revenue due to the impact on parts of theturbine such as combustion, hot gas parts and rotor life. For example,changes to the fuel temperature, such as lowering it, can increaseoutput and lower efficiency, but have no impact on maintenance andavailability, and thus, do not adversely affect the operational revenue.

FIG. 2 is a block diagram of an example of a dispatch advisor system 18for operating a power plant having at least one gas turbine withflexibility in accordance with an embodiment of the present invention.Aspects of the dispatch advisor system 18 including methods, processes,and operations performed thereby can constitute machine-executablecomponents embodied within machine(s), e.g., embodied in one or morecomputer-readable mediums (or media) associated with one or moremachines. Such components, when executed by one or more machines, e.g.,computer(s), computing device(s), automation device(s), virtualmachine(s), etc., can cause the machine(s) to perform the operationsdescribed.

Further, the description that follows for the dispatch advisor system 18in FIG. 2, as well as the description associated with other figures mayuse the terms “object,” “module,” “interface,” “component,” “system,”“platform,” “engine,” “selector,” “manager,” “unit,” “store,” “network,”“generator” and the like to refer to a computer-related entity or anentity related to, or that is part of, an operational machine orapparatus with a specific functionality. These entities can be eitherhardware, a combination of hardware and firmware, firmware, acombination of hardware and software, software, or software inexecution. In addition, entities identified through the above terms areherein generically referred to as “functional elements.” As an example,a component can be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. By way of illustration, both anapplication running on a server and the server can be a component. Oneor more components may reside within a process and/or thread ofexecution, and a component may be localized on one computer and/ordistributed between two or more computers. Also, these components canexecute from various computer-readable storage media having various datastructures stored thereon. The components may communicate via localand/or remote processes such as in accordance with a signal having oneor more data packets (e.g., data from one component interacting withanother component in a local system, distributed system, and/or across anetwork such as the Internet with other systems via the signal). As anexample, a component can be an apparatus with specific functionalityprovided by mechanical parts operated by electric or electroniccircuitry, which is operated by software, or firmware applicationexecuted by a processor, wherein the processor can be internal orexternal to the apparatus and executes at least a part of the softwareor firmware application. As another example, a component can be anapparatus that provides specific functionality through electroniccomponents without mechanical parts. The electronic components caninclude a processor therein to execute software or firmware that confersat least in part the functionality of the electronic components.Interface(s) can include input/output (I/O) components as well asassociated processor(s), application(s), or API (Application ProgramInterface) component(s). While examples presented hereinabove aredirected to a component, the exemplified features or aspects also applyto object, module, interface, system, platform, engine, selector,manager, unit, store, network, and the like.

Referring again to FIG. 2, the dispatch advisor system 18 can include aflexible base load map generation component 20, an operational revenueoptimizing component 22, an optimized revenue—flexible base loadvisualization component 24, a service and maintenance optimizingvisualization component 26, a user interface component 28, one or moreprocessors 30, and memory 32 that stores data 34. In variousembodiments, one or more of the flexible base load map generationcomponent 20, the operational revenue optimizing component 22, theoptimized revenue—flexible base load visualization component 24, theservice and maintenance optimizing visualization component 26, the userinterface component 28, the one or more processors 30, and the memory 26can be electrically and/or communicatively coupled to one another toperform one or more of the functions of the dispatch advisor system 18.In some embodiments, one or more of the flexible base load mapgeneration component 20, the operational revenue optimizing component22, the optimized revenue—flexible base load visualization component 24,the service and maintenance optimizing visualization component 26, andthe user interface component 28 can comprise software instructionsstored on the memory 32 and executed by processor(s) 30. In addition,the dispatch advisor system 18 may interact with other hardware and/orsoftware components not depicted in FIG. 2. For example, processor(s) 30may interact with one or more external user interface devices, such as akeyboard, a mouse, a display monitor, a touchscreen, or other suchinterface devices.

The flexible base load map generation component 20 can be configured togenerate or obtain a flexible base load map for operating a power planthaving at least one gas turbine to meet base load power demands. Theflexible base load map can include an operating space for operating thepower plant according to a plurality of operational parameters. In oneembodiment, the operational parameters can include the firingtemperature of the gas turbine and position of inlet guide vanes in thegas turbine, and the fuel temperature of the fuel in the gas turbine.The flexible base load map can include a primary base load operatingspace obtained from a first set of the operational parameters thatprovides power output and efficiency values of the power plant that areattained over an operating space of the first set of operationalparameters. In one embodiment, the first set of operational parameterscan include the firing temperature and the position of the inlet guidevanes. In general, the primary base load operating space is indicativeof a primary operating space to attain target plant power output andefficiency. The flexible base load map can further include an expandedportion that provides an operating space that relates to a second set ofthe operational parameters of the power plant. In one embodiment, thesecond set of the operational parameters can include the firingtemperature, the position of the inlet guide vanes, and the fueltemperature. In general, the expanded portion of the base load operatingspace is indicative of a secondary operating space that attains higherplant power output and sub-optimal efficiency in relation to the primarybase load operating space.

The flexible base load map generation component 20 can also beconfigured to partition the flexible base load map into a plurality ofoperating segments. To this extent, each operating segment correspondsto a particular portion of the operating space that is represented inthe flexible base load map. Each segment is characterized by a range ofoperating values for the operational parameters and corresponding poweroutput and efficiency values that are attained while operating the powerplant at the range of operating values in the operating segment.

The operational revenue optimizing component 22 can be configured todetermine the revenue that is generated from operating the power plantbased on the flexible base load map obtained by the flexible base loadmap generation component 20. In one embodiment, the operational revenueoptimizing component 22 can determine the operational revenue for eachof the partitioned operating segments over the entire operating spacerepresented by the flexible base load map. In particular, theoperational revenue optimizing component 22 can determine theoperational revenue for each of the segments based on the range ofoperating values in the segments and the corresponding power output andefficiency values that are attained for those operating values, whiletaking into consideration at least one of a plurality of marketconditions associated with a power generation market. The plurality ofmarket conditions can include any of a number of conditions that canaffect the revenue generated by a power plant. These market conditionscan include, but are not limited to, capacity market pricing, spotmarket pricing, energy market pricing, the capacity or power output thatthe power plant provides, the capacity rate, fuel prices, and CO2 taxes.In one embodiment, the operational revenue optimizing component 22 candetermine the operational revenue for each of the segments byascertaining income from capacity payments for capacity or powercommitments entered into over a capacity market, and income from powersold at a spot market, and debiting the sum of the total income with theexpenses of operating the power plant that include fuel expenses,service and maintenance expenses, and CO2 taxes.

The optimized revenue—flexible base load visualization component 24 canbe configured to map the revenue determinations for each of theoperating segments with the operating space provided by the flexiblebase load map in order to provide a visual representation of theoperational revenue that is generated for each of the operatingsegments. The optimized revenue—flexible base load visualizationcomponent 24 can generate a visual representation of the revenue for theflexible load map including each of the operating segments for themarket conditions that were evaluated. In one embodiment, the pluralityof visual representations that can be generated can include interactivevisualizations that enable direct manipulation and exploration ofrepresentations of data in the visualizations with respect to revenuepossibilities from operating the power plant to one more of theplurality of market conditions.

The service and maintenance optimizing visualization component 26 can beconfigured to generate visualizations that depict the impact that theoperating space of the flexible base load map will have on themaintenance and service of parts of the power plant based on theoperating conditions associated with each of the operating segments. Inone embodiment, the service and maintenance optimizing visualizationcomponent 26 can be configured to use the visualizations generated fromthe optimized revenue—flexible base load visualization component 24 andprovide a visual representation that provides an indication that suchoperating conditions in the revenue transposed flexible base load mapwill have on the service and maintenance of the various parts andcomponents in the power plant. For example, the service and maintenanceoptimizing visualization component 26 can determine and note thatcertain higher firing temperatures, although helpful in increasing poweroutput, will come at a price to the service and maintenance of the powerplant because such high temperatures will reduce the life cycle ofparts, and require maintenance costs to keep running and eventualreplacement costs. As a result, the service and maintenance optimizingvisualization component 26 can provide indications of other operatingsegments that will have less impact on service and maintenance, andoverall better operational revenue.

The user interface component 28 can be configured to receive user inputand to render output to the user in any suitable format (e.g., visual,audio, tactile, etc.). In some embodiments, the user interface component28 can be configured to generate a graphical user interface that can berendered on a client device that communicatively interfaces with thedispatch advisor system 18, or on a native display component of thesystem 18 (e.g., a display monitor or screen). Input data can include,for example, base load data related to the operational parameters of thepower plant during base load at a plurality of base load settings atpredetermined ambient conditions. As noted above, in one embodiment, theoperational parameters can include the firing temperature of the gasturbine, the position of the inlet guide vanes in the gas turbine, andthe fuel temperature of the fuel in the gas turbine. In addition to thebase load settings of these operational parameters, the input data caninclude the power output and efficiency values that are attained by thepower plant while operating at each of the base load settings at thepredetermined ambient conditions during base load. It is understood thatthe input data can include other data related to other operationalparameters. Moreover, it is understood that although the variousembodiments are described with respect to parameters that include thefiring temperature, the position of the inlet guide vanes, and the fueltemperature, other operational parameters such as temperature, pressure,humidity and gas flow characteristics at locations defined along thepath of the working fluid, as well as ambient conditions, fuelcharacteristics, and other measurables can be used to generate theflexible base load map. In addition to the aforementioned data, theinput data can include, for example, user-defined constraints to betaken into account when generating the flexible base load map (e.g.,upper and lower limits on gas turbine operating temperature or poweroutput, definition of a desired operating horizon, definition of ambientconditions, identification of days during which the gas turbines are notallowed to run, etc.).

In addition, the input data can include market data such as spot marketpricing, capacity market pricing, and energy market pricing. Other inputdata can include operating expenses that include but are not limited to,fuel pricing, service and maintenance costs of power plant componentsand parts including replacement costs, and taxes and fees such as CO2penalties.

The output data that can be rendered by the user interface component 28can include, but are not limited to, graphical renderings of one or morerepresentations of the flexible base load map for operating the powerplant that is generated by the flexible base load map generationcomponent 20. As noted above, these visualizations can includerepresentations pertaining to the operational revenue associated withthe generated flexible base load map, and representations pertaining tothe service and maintenance of the power plant. Other output data thatcan be provided by the user interface component 22 can include, forexample, text-based or graphical renderings of a plant asset operatingprofile or schedule. It is understood that both the input data and theoutput data can be stored in memory 32 as part of the stored data 34.

The one or more processors 30 can perform one or more of the functionsdescribed herein with reference to the systems and/or methods disclosed.The memory 32 can be a computer-readable storage medium that can storecomputer-executable instructions and/or information for performing thefunctions described herein with reference to the systems and/or methodsdisclosed.

Additional details of the flexible base load map generation component20, the operational revenue optimizing component 22, the optimizedrevenue—flexible base load visualization component 24, and the serviceand maintenance optimizing visualization component 26, the userinterface component 28, the one or more processors 30, memory 32, andthe stored data 34 are presented below.

Although features of the dispatch advisor system 18 are described hereinwith reference to gas turbines, it is to be appreciated that embodimentsof the dispatch advisor system 18 are not limited to use solely with gasturbines, but rather can be used to generate a flexible base load maphaving an extended operating space, maximize operational revenue,forecast operational scenarios, manage outages and availability whileachieving maximum revenue, that is suitable for other types ofpower-generating assets.

FIG. 3 is a block diagram 36 illustrating example data inputs andoutputs for the flexible base load generation component 20 of thedispatch advisor system 18 depicted in FIG. 2 in accordance with anembodiment of the present invention. More particularly, the blockdiagram of FIG. 3 illustrates that the flexible base load generationcomponent 20 is configured to utilize one or more algorithms 38 foroperating on base load parameter data 40 to generate a flexible baseload map 42. Although the description that follows is directed towardsthe generation a flexible base load map 42, the flexible base loadgeneration component 20 of the dispatch advisor system 18 describedherein can obtain a previously generated flexible base load map 42.

The base load parameter data 40 can include, for example, base load datarelated to the operational parameters of the power plant during baseload at a plurality of base load settings at predetermined ambientconditions. As noted above, in one embodiment, the operationalparameters can include the firing temperature of the gas turbine, theposition of the inlet guide vanes in the gas turbine, and the fueltemperature of the fuel in the gas turbine. In addition to the base loadsettings of these operational parameters, the base load parameter data40 can include the power output and efficiency values that are attainedby the power plant while operating at each of the base load settings atthe predetermined ambient conditions. With the base load parameter data40, the algorithm(s) 38 of the flexible base load generation component20 can generate the flexible base load map 42. Further details of thealgorithm(s) 38 and the flexible base load map 42 are discussed belowwith reference to FIGS. 4 and 5, respectively.

As shown in FIG. 4, the algorithm 38 to generate the flexible base loadmap 42 begins at 44 where a plurality of base load data related tooperational parameters of the power plant during base load, at aplurality of base load settings, at predetermined ambient conditions,are obtained. In one embodiment, the operational parameters for whichthe base load data is obtained can include, but are not limited to, thefiring temperature of the gas turbine, the position of inlet guide vanesin the gas turbine, and the fuel temperature of the fuel in the gasturbine.

The obtaining of the base load data can include receiving, gathering oracquiring the data using any of a number of well-known approaches. Inone embodiment, the base load data can reside in data libraries,resources and repositories, which may be referred to herein generally as“data resources” that are connected to the dispatch advisor system 18,and in particular, the flexible base load map generation component 20via communications lines or over which data is exchanged in thisembodiment and others disclosed herein. The data resources may includeseveral types of data, including but not limited to, operating datarelating to the operational parameters, and ambient data. The ambientdata can include information related to ambient conditions at the plant,such as ambient air temperature, humidity, and/or pressure. Theoperating, and ambient data each may include historical records, presentcondition data, and/or data relating to forecasts. For example, dataresources may include present and forecast meteorological/climateinformation, present and forecast market conditions, usage andperformance history records about the operation of the power plant,and/or measured, observed, or tracked parameters regarding the operationof other power plants having similar components and/or configurations,as well as other data as may be appropriate and/or desired. Thecommunications lines may be wired or wireless, and further, it will beappreciated that the data resources and the dispatch advisor system 18may be connected to or be part of a larger communications system ornetwork, such as the internet or a private computer network.

The algorithm of FIG. 4 continues at 46 where the base load data iscorrelated to power output and efficiency values. In one embodiment, thebase load data for the operational parameters at each of the pluralityof base load settings at the predetermined ambient conditions duringbase load are correlated to the power output and efficiency values thatare attained by the power plant for each of the respective values. Tothis extent, the flexible base load map generation component 20 canascertain the power output and efficiency values that are attained bythe power plant for each of the values of the operational parameters ateach of base load settings.

With this correlation of data, the algorithm run by the flexible baseload map generation component 20 can determine a primary base loadoperating space at 48. In one embodiment, this primary base loadoperating space is indicative of a primary operating space that enablesthe power plant to attain target plant power output and efficiency. Tothis extent, a plant operator can use the primary base load operatingspace to operate a power plant during base load in a manner thatachieves a target output and efficiency.

In one embodiment, the primary base load operating space can bedetermined from a first set of the operational parameters used in thecorrelation of the data. To this extent, the primary the base loadoperating space provides a representation that associates the poweroutput and efficiency values of the power plant that are attained withthe first set of operational parameters while operating at each of theplurality of base load settings at the predetermined ambient conditionsduring base load. In one embodiment, the first set of operationalparameters can include the firing temperature and the position of theinlet guide vanes.

After determining the primary base load operating space, a secondarybase load operating space can be formed at 50 by expanding upon theprimary base load operating space. The secondary base load operatingspace can be formed from a second set of the operational parameters usedin the correlation of the data. For example, the second set of theoperational parameters can include the firing temperature, the positionof the inlet guide vanes, and the fuel temperature. In one embodiment,the secondary base load operating space is representative of an expandedportion of the primary base load operating space that attains higherplant power output and less than optimal or sub-optimal efficiency inrelation to the primary base load operating space. To this extent, aplant operator can use the secondary base load operating space tooperate a power plant during base load to achieve different targets inscenarios where it may not be desirable to operate the plant at a highoutput and efficiency. For example, a plant operator can use thesecondary base load operating space to maximize capacity payments forcapacity or power commitments entered into over a capacity market at anexpense of yielding maximum revenue due to lower efficiency and impacton service life of components of the power plant.

The operations of the algorithm 38 of the flexible base load mapgeneration component 20 can continue at 52 where the primary base loadoperating space and the secondary base load operating space areaggregated to form a flexible base load map for operating the powerplant. In one embodiment, the representation of the flexible base loadmap offers a range of operating values for the operational parametersand corresponding power output and efficiency values that are attainedwhile operating the power plant at the range of operating values. Withthis representation containing both the primary base load operatingspace and the secondary base load operating space, the resultingflexible base load map offers an operator of a power plant withflexibility in controlling the power plant during base load. Inparticular, the resulting representation provides a first operatingspace (i.e., the primary base load operating space) that the operatorcan use to attain target plant power output and efficiency, and a secondoperating space that attains higher plant power output and less thanoptimal or sub-optimal efficiency in relation to the first operatingspace, which offer the operator the option to control the plant inaccordance with other objectives that are not concerned with high outputand high efficiency (e.g., to maximize capacity payments). Thisaggregation of the primary base load operating space and the secondarybase load operating space can be presented to a plant operator at 54 inthe form of a visual representation such as a flexible base load map, ofwhich an example is depicted in FIG. 5.

FIG. 5 is an example of a representation of a flexible base load map 42for operating the power plant that can be generated by the flexible baseload generation component 20 of the dispatch advisor system 18 using theoperations depicted in FIG. 4 in accordance with an embodiment of thepresent invention. FIG. 5 shows the flexible base load map 42 with anoperating space defined by operational parameters which can include thefiring temperature (TFire) of the gas turbine, the Mach number (Mn)which corresponds to the IGVs position in the gas turbine, and the fueltemperature (TFuel) of the fuel in the gas turbine. As shown in FIG. 5,the flexible base load map 42 can comprise a multi-dimensionalrepresentation of these operational parameters. In particular, themulti-dimensional representation of the flexible base load map 42 inFIG. 5 differentiates a primary base load operating space 56 from theexpanded portion 58 of the base load operating space which isrepresentative of the secondary base load operating space. FIG. 5 showsthat the multi-dimensional representation of the flexible base load map42 comprises a three-dimensional representation of the operationalparameters (e.g., TFire, Mn, and TFuel) and a two-dimensionalrepresentation of the power output and efficiency values, which aredenoted as A Output and A Efficiency, respectively. In one embodiment,the three-dimensional representation of the operational parametersTFire, Mn, and TFuel is juxtaposed with the two-dimensionalrepresentation of the power output and efficiency values A Output and AEfficiency. As shown in FIG. 5, the three-dimensional representation ofthe operational parameters in the flexible base load map 42 comprises afirst axis representative of values associated with the firingtemperature TFire, a second axis representative of values associatedwith the position of the inlet guide vanes Mn, and a third axisrepresentative of values associated with the fuel temperature TFuel,whereas the two-dimensional representation of the power output andefficiency values comprises a first axis representative of the poweroutput values, A Output, and a second axis representative of theefficiency values, A Efficiency.

In the example depicted in FIG. 5, the flexible base load map 42 showsthat the firing temperature TFire, the Mach number Mn, and the fueltemperature TFuel are variable in this base load operating space whichcovers the primary base load operating space 56 and the expanded portion58. As shown in FIG. 5, the firing temperature TFire can range from 2830F to 2865 F, while the Mach number Mn ranges from 0.8 to 0.84, and thefuel temperature TFuel can range from 600 F in the region where theprimary base load operating space 56 adjoins with the expanded portion58 containing the secondary base load operating space to 200 F at theregion furthest away from the adjoining section.

With this flexible base load map 42 showing an operating space ofoptimum operating conditions for operating a power plant such as, forexample, a combined-cycle power plant, a plant operator can use theoperating space as guidance to select specific settings of operationalparameters of the power plant during base load at predetermined ambientconditions. To this extent, depending on the desired objectives of howthe power plant is to be operated, the plant operator can select valuesfor the firing temperature TFire, the Mach number Mn, and the fueltemperature TFuel that will result in the type power output andefficiency that meets these objectives. For example, if the plantoperator desires to operate the power plant to achieve target output andefficiency, the operator could focus on using the operating space in theflexible base load map 42 that is covered by the primary base loadoperating space 56. To this extent, the operator can use the increasedoperating space of firing temperature TFire and the Mach number Mn,which extends from 2830 F to 2865 F and from 0.8 to 0.84, respectively,to adjust TFire and Mn values in a manner that achieve a target outputand efficiency while satisfying a particular objective or interest. Thiscan include adjusting the target plant load and efficiency toaccommodate scenarios where it is desirable to maximize revenue,forecast operational scenarios, manage outages and availability,purchase fuel, and plan for service and maintenance.

In another example of use of the flexible base load map 42 depicted inFIG. 5, the plant operator can use the expanded portion 58 of the baseload operating space that is indicative of the secondary base loadoperating space to select optimum conditions for the firing temperatureTFire, Mach number Mn and the fuel temperature TFuel, in those instanceswhere it is desired to run at a higher output, but at sub-optimalefficiency. For example, a plant operator could choose to operate thepower plant at a firing temperature TFire of 2865 F, a Mach number Mn of0.84, and a fuel temperature TFuel of 200 F. In this scenario, as notedin FIG. 5, the output of the power plant would have increased such thatthere is a 4.3% increase in capacity in comparison to the point depictedin the figure with the star that operates at a firing temperature TFireof 2830 F and a Mach number Mn of 0.8. However, this increased outputwould come at a decrease in efficiency of the power plant. Suchoperating scenarios where operating at an increased output, but at asub-optimal efficiency, may be desirable in certain instances. Theseinstances could arise in circumstances that can include, but are notlimited to, maximizing revenue, forecasting operational scenarios,managing outages and availability, purchasing fuel, and planning forservice and maintenance. For example, in one embodiment, the operatorcan adjust the firing temperature TFire, the Mach number Mn, and thefuel temperature TFuel values in the secondary base load space in amanner where output and efficiency are not the primary objectives. Inone embodiment, the plant operator can adjust the firing temperatureTFire, the Mach number Mn, and the fuel temperature TFuel values in thesecondary base load space of the flexible base load map 40 to maximizeoperational revenue in a spot market by selling power that allows forthe highest possible capacity payments. In some instances, this can beof interest to power plant operators even despite the effect that therewill be sub-optimal efficiency.

FIG. 6 is a block diagram 60 illustrating example data inputs andoutputs for the operational revenue optimizing component 22 of thedispatch advisor system 18 depicted in FIG. 2 in accordance with anembodiment of the present invention. More particularly, the blockdiagram of FIG. 6 illustrates that the operational revenue optimizingcomponent 22 is configured to utilize one or more algorithms 62 foroperating on flexible base load map parameter data 64, economic data 66,maintenance and service data 68, and miscellaneous data 70 to generatean optimized revenue map 72 for each of the operating segmentsrepresented in the flexible base load parameter map data 64.

The flexible base load map parameter data 64 can include, for example,base load data related to the operational parameters of the power plantduring base load at a plurality of base load settings at predeterminedambient conditions. This includes the base load for the operationalparameters such as the firing temperature of the gas turbine, theposition of the inlet guide vanes in the gas turbine, and the fueltemperature of the fuel in the gas turbine. In addition to the base loadsettings of these operational parameters, the flexible base load mapparameter data 64 can include the power output and efficiency valuesthat are attained by the power plant while operating at each of the baseload settings at the predetermined ambient conditions during base load.In addition, the flexible base load map parameter data 64 includes thepartitioned operating segments and their corresponding operationalparameter, power output and efficiency values.

The economic data 66 can include data related to market conditionsassociated with a power generation market that can affect the revenuegenerated by a power plant. The data can include, but not limited to,capacity market pricing, spot market pricing, energy market pricing, thecapacity or power output that the power plant provides, the capacityrate, fuel prices, and CO2 taxes.

The maintenance and service data 68 can include data related to themaintenance and service of a power plant. This can include data such asservice and maintenance costs of power plant components and partsincluding replacement costs. The maintenance and service data 68 caninclude historical costs as well as expected costs that are associatedwith running a power plant at any of the various operational settingsfor the operational parameters (e.g., firing temperature, IGV positions,fuel temperature). Other maintenance and service data 68 can include thelife cycle or wear life of the components that is expected with runninga power plant at any of the various operational settings for theoperational parameters (e.g., firing temperature, IGV positions, fueltemperature).

The miscellaneous data 70 can include data that relates to the operationof a power plant and that may have a role in impacting the revenue thatis generated by the power plant. For example, the miscellaneous data 70can include ambient temperature data such as climate changes that canconstrain power supply, transmission capacity, and demand. The ambienttemperature data in the miscellaneous data 70 can include historicaldata and forecasted data, as well as information that indicates theeffects that the temperature has had on power supply, transmissioncapacity, demand, and revenue. Other miscellaneous data 70 can includedata that pertain to individual power plants. For example, this caninclude the maximum capacity of the power plants, the heat rates of thepower plants, component configuration of the power plants, and the like.

Below is a further description of some of the data described above thatcan be stored in the economic data 66, the maintenance and service data68, and the miscellaneous data 70 depicted in FIG. 6, and how the datacan be obtained. It is understood that the descriptions of the data areillustrative and not meant to be limiting as those skilled in the artwill appreciate that other options for obtaining, producing or derivingthe data exist.

The power output of a power plant such as a combined-cycle power plantoutput can be obtained thru simulation of a power plant using asimulation software application such as EBSILON. In one embodiment, thesimulation can be carried out across an ambient range, where theflexible base load is provided. In this example, it is reasonable toassume 2 C for ambient steps increments. Those skilled in the art willappreciate that linear interpolation between ambient can be used.

The power plant heat rate of a plant such as a combined-cycle powerplant can be obtained from the same simulations used to simulate theperformance of the plant including its power output noted above. Linearinterpolation is suggested across ambient. It is understood that it ispossible to incorporate the effect of degradation, as there are severalscenarios of how it can be done.

The maximum capacity (MW) and capacity payment ($/kw-yr) data can beboth obtained as values inputted by a plant operator. Although maximumcapacity and capacity payments are not expected to changeinstantaneously, it is understood that in some applications it may besubject for year-to year or seasonal variation and can be adjusted by anoperator as appropriate.

Spot market instantaneous power price ($/MW-hr) data is another type ofdata that can be inputted by the operator.

Fuel price ($/MMBTU (HHV) data is another type of data that can beinputted by the operator.

The instantaneous CO₂ tax rate ($/ton) data is another type of data thatcan be inputted by the operator. In general, the CO₂ tax is subject tolocal and industry regulations. It is expected to vary widely based onlocation, power demand and other factors. In one embodiment, the CO₂ taxrate can be calculated based on the following equation:

${\frac{{CC}{output}({kW})*{CC}{Heat}{Rate}\frac{kJ}{kWh}*56.1}{1000000000}*C{O2}{tax}{rate}\left( \frac{\$}{ton} \right)},$

wherein 56.1 tonCO₂/TJ is a CO₂ emissions factor for natural gas perACER regulation.

It is understood that the service pricing can be based on a multiple offactors. For example, the service pricing can be noted at differentlevels of overfire over the duration of a customer service agreement(CSA) that a power plant may have. In one embodiment, the servicepricing numbers can be obtained by modeling specific service contractsusing a modeling software package like MINI, assuming overfire amaintenance factor (MF) applies thru the entire duration of thecontract. To this extent, a per hour rate ($/hr) can be derived based oncontract duration. This number can represent an effect of overfire oncombustion and hot gas path hardware. For example, a cost of 2MI(128,000 AFH) CSA contract with MF=1 (no overfire) is$61,977,773/128,000 AFH, results in a 483.94 $/hr A cost of a 2-MI(128,000 AFH) contract with peak firing at 2865 F (MF=2.23) is$149,838,286. Therefore, an hourly rate of 1170.6 $/hr can be obtained.As a result, these numbers can become a base cost for different levelsof overfire.

Replacement costs of components and their maintenance factors such asfor example, a rotor replacement can be based on compressor dischargetemperature (Tcd) and exposure time. In one embodiment, rotorreplacement cost is a constant that can be obtained from a CSA regionalteam. It is understood that when IGVs are moved to a more open position(high Mn), the compressor discharge temperature (Tcd) increases.Increases in Tcd above certain point, triggers rotor life malfunctionMF. In one embodiment, a rotor MF can be estimated based on the Tcdrange:

850 F<Tcd<950 F: MF=(0.0007395 Tcd²−0.7316 Tcd+0.0002742)/(Tcd−958.6)Tcd<850 F: MF=0.8.

As an example, the expected rotor replacement life can be determined as160,000 hrs and its cost is $8,222,369.60. In this example, a rotorMF=1.14 for Mn=0.84. Thus, per hour rotor life impact can be describedby the following expression:

${\frac{{\$ 8},222,36{9.6}0}{160,000{hr}}*{1.1}4} = {58.58\$/{{hr}.}}$

As a result, the total services impact of operation in a particularoperating segment of the flexible base load can be a sum of hourly ratesfor base CSA cost for an overfire scenario and hourly rate of rotor lifeimpact.

The ambient conditions data, which can be used for performancecorrection of the power plant, can be fed or obtained from databasesthrough typical data retrieval techniques or inputted by the operator.

With the flexible base load map parameter data 64, the economic data 66,the maintenance and service data 68, and the miscellaneous data 70, thealgorithm(s) 62 of the operational revenue optimizing component 22 cangenerate the optimized revenue 72 for each of operating segmentsrepresented in the flexible base load parameter map data 64.

Further details of the algorithm(s) 62 and the operational revenueoptimizing component 22 are discussed now with reference to FIG. 7. Asshown in FIG. 7, the algorithm 62 for optimizing operational revenuebegins at 74 where the partitioned operating segments generated by theflexible base load map generation component 20 are obtained. For each ofthe of operating segments, the income that is earned from operating thepower plant over the range of operating values with the correspondingpower output and efficiency values is ascertained at 76 for a pluralityof market conditions. In one embodiment, the income that can beascertained includes capacity payments, spot market pricing and energymarket pricing. It is understood that capacity payments, spot marketpricing and energy market pricing are analogous to specific marketconditions, however, embodiments are not meant to be limiting as thereother market conditions that can affect the revenue, and thus, theincome of the power plant, can include the capacity or power output thatthe power plant provides, the capacity rate, fuel prices, and CO2 taxes.

In addition to determining the income, the expenses of operating thepower plant over each of the operating segments can be ascertained at78. The expenses can comprise one or more of fuel expenses associatedwith purchasing fuel for operating the power plant, carbon taxes foremissions created from use of fossil fuels for power generation, andservice expenses associated with servicing and maintenance of the powerplant. The algorithm 62 can obtain maintenance and service data andeconomic data such as that described and depicted with respect to FIG.6.With the income and expenses ascertained the revenue for each of theoperating segments can be determined at 80. In general, the revenue overeach of the plurality of operating segments can be determined bydebiting a sum of the income from the capacity payments, the income frompower sold at a spot market and the income power sold in the energymarket with the expenses of operating the power plant in the segments.In one embodiment, revenue can be determined in accordance with thefollowing equation:

R=(CI+P1)−FE+CO₂ Tax+SE), wherein

R is revenue from operations;CI is income from capacity payments;PI is income from power sold at a spot market;FE is expenses associated with purchasing fuel;CO₂ Tax is the CO₂ tax rate that may be levied by a regulatoryauthority; andSE is expenses associated with service and maintenance.It is understood that this revenue equation represents only one exampledemonstrating how revenue can be determined. It is not meant to belimiting, as those skilled in the art will appreciate that there aremany equations that can be used to determine revenue. In addition, it isunderstood that the parameters used in the above revenue equation tocalculate revenue represent an example of some parameters that can beused, and is not meant to be limiting to the various embodiment. Thoseskilled in the art will appreciate that the parameters can depend on thetype of income that is earned by the power plant and the specificexpenses that are incurred while running the plant.

Once the revenue has been ascertained for all of the operating segments,the revenue associated with the segments are compiled into an optimizedrevenue map at 82. In an embodiment, the optimized revenue map caninclude the flexible base load map partitioned into operating segments,with each segment containing a range of values for the operationalparameters and the corresponding efficiency and output values that areattained with the values of the parameters, and data containing ameasurement of the operational revenue that can be earned over amultiple of different market conditions.

FIG. 8 is a block diagram 84 illustrating example data inputs andoutputs for the optimized revenue/flexible base load map visualizationcomponent 24 of the dispatch advisor system depicted in FIG. 2 inaccordance with an embodiment of the present invention. Moreparticularly, the block diagram 84 of FIG. 8 illustrates that theoptimized revenue/flexible base load map visualization component 24 isconfigured to utilize one or more algorithms 86 for operating on theflexible base load map 42 generated by the flexible base load generationcomponent 20 and the optimized revenue map 72 generated by theoperational revenue optimizing component 22, to generate a visualizationof the revenue determinations for each of the operating segments withthe operating space provided by the flexible base load map in order toprovide optimized revenue/flexible base load map visualizations 88. Ingeneral, the algorithm 86 maps the optimized revenue map 72 within theoperating space of the flexible base load map 42, and generates a visualrepresentation for each of the evaluated market conditions. To thisextent, each visualization for a particular market condition can includea representation of not only the operating segments of the flexible baseload operating space with operational parameters with correspondingoutput and efficiency, but also the operational revenue that isgenerated for each of the operating segments. In one embodiment, thevisual representations can include interactive visualizations thatenable direct manipulation and exploration of representations of data inthe visualizations with respect to revenue possibilities from operatingthe power plant to one more of the plurality of market conditions.

FIG. 9 is flow chart that describes examples of operations performed bythe algorithm 86 that is utilized by the optimized revenue/flexible baseload map visualization component 24 to generate the visualizations 88depicted in FIG. 8. As shown in FIG. 9, the algorithm 86 can begin at 90where the compiled optimized revenue map generated by the operationalrevenue optimizing component 22 is obtained. In addition, the flexiblebase load map generated by the flexible base load generation component20 can be obtained at 92. Next, the optimized revenue map is mapped withthe flexible base load map at 94 for each evaluated market condition. Inone embodiment, the optimized revenue map can be mapped with theflexible base load map for each evaluated market condition by well-knownmapping applications that are commercially available. After themappings, a visual representation of each mapping can be generated at 96by well-known visualization applications that are commerciallyavailable.

FIG. 10 is an example showing a visualization 98 of an optimized revenuemap within a flexible base load map in accordance with an embodiment ofthe present invention. In one embodiment, the visualization can includea two-dimensional array 100 partitioned to show the various operatingsegments obtained from the flexible base load map. As shown in FIG. 10,the two-dimensional array 100 can comprise a first axis representativeof values associated with the firing temperature (TFire), and a secondaxis representative of values associated with both the position of inletguide vanes (IGV) in the gas turbine, and the fuel temperature (TFuel)of the fuel in the gas turbine. The two-dimensional array 100 canfurther include a representation of the efficiency values on the firstaxis and a representation of the output values on the second axis.

The visualization 98 can further include a visual representation of therevenue that can be earned throughout each of the plurality of operatingsegments. In particular, the visual representation of the revenue foreach operating segment is representative of an amount of revenue that ispossible from operating the power plant based on the range of operatingvalues and power output and efficiency values that are attained with theoperating values for a respective operating segment. In one embodiment,the visual representation of the revenue can be based on a plurality ofvisual revenue indicators. In this manner, each visual revenue indicatorcan be representative of an amount of revenue that is possible fromoperating the power plant based on the range of operating values andpower output and efficiency values that are attained with the operatingvalues for a respective operating segment. In one embodiment, theplurality of visual revenue indicators can comprise a spectrum ofrevenue visual indicators having a low-end revenue visual indicator, ahigh-end revenue visual indicator and one or more intermediary revenuevisual indicators extending from the low-end revenue visual indicator tothe high-end revenue visual indicator. The intermediary revenue visualindicators that are closer to the low-end revenue visual indicator canbe indicative of lower revenue and the intermediary revenue visualindicators that are closer to the high-end revenue visual indicator canbe indicative of higher revenue. In one embodiment, the amount ofrevenue associated with the intermediary revenue visual indicators canincrease progressively from the intermediary revenue visual indicatorsthat are closer to the low-end revenue visual indicator to theintermediary revenue visual indicators that are closer to the higher-endrevenue visual indicator.

As shown in FIG. 10, this spectrum of revenue visual indicators can berepresented by shading. In FIG. 10, this spectrum of revenue visualindicators can include dotted patterns with the various densities ofdotted patterns each representative of a particular amount of revenue.For example, the dotted patterns of a lesser density (e.g., lower leftcorner and in the vicinity thereof) can represent high amounts ofrevenue, the dotted patterns of a higher density and darker shading(e.g., upper right corner and in the vicinity thereof) can represent lowamounts of revenue, and the dotted patterns of a varying density thatrange between the dotted patterns of the lower density and the higherdensity, can represent varying amounts of intermediary amounts ofrevenue that are less than the high amounts of revenue and greater thanthe low amounts of revenue.

It is understood that the visual indicators depicted in FIG. 10 arerepresentative of one possibility and are not meant to be limiting dueto the numerous possibilities that could be deployed to representgradations in the amount of revenue. For example, a color-coded schemecould be used to represent the revenue. In one embodiment, green shadingcould be used to represent operating segments with the potential to earnthe highest amount of revenue, red shading could be used to representoperating segments with the potential to earn the lowest amount ofrevenue, while lighter shading of green and red could be used torepresent operating segments with the potential to earn the amount ofrevenue that is less than the highest revenue earning segment, andgreater than the lowest revenue earning segment, respectively.

Regardless of the type of indicators that are used, the visualizationgenerated for each of the various market conditions according to thevarious embodiments, can be arranged as a guide and presented to anoperator of a power plant. To this extent, the operator can use one ormore of the visualizations to select the optimum operating conditionsfor the power plant to meet base load power demands, while at the sametime earning a maximized revenue based on instantiations of the marketconditions.

Although not depicted in the visualization shown in FIG. 10, thevisualizations that are generated according to the various embodimentscan include interactive visualizations that enable direct manipulationand exploration of representations of data in the visualizations withrespect to revenue possibilities from operating the power plant to onemore of the plurality of market conditions. In one embodiment, thevisualizations can be appended with one or more user interactive sliderscales configured to receive user-input for moving about each of theoperating segments, and one or more input and output buttons forreceiving user input data and displaying output data. In this manner anoperator can move each of the one or more user interactive slider scalesto control at least one of the plurality of operational parameters. Tothis extent, the manipulation of each of the one or more userinteractive slider scales will show a change in revenue that arises withan accompany change to the at least one of the plurality of operationalparameters.

In one embodiment, the one or more user interactive slider scales cancomprise a first interactive slider scale that is configured to receivechanges to the firing temperature (TFire) and a second interactiveslider scale that is configured to receive changes to the position ofthe inlet guide vanes (IGVs) in the gas turbine, and the fueltemperature (TFuel) of the fuel in the gas turbine. For example, thefirst interactive slider scale and the second interactive slider scalecan be configured for movement towards an operating segment thatprovides maximum revenue.

In another example, the one or more input and output buttons can beconfigured to receive operating data associated with the operationalparameters of the power plant, and target power output and efficiencyvalues. This allows an operator to modify the visualizations based onany data received by the one or more input and output buttons, and besubsequently presented with a modified visualization. The firstinteractive slider scale and the second interactive slider scale arealso configured to allow movement about the modified visualization. Thismovement of one or more of the first interactive slider scale and thesecond interactive slider scale can result in a display of an outputvalue associated with the power plant on the one or more input andoutput buttons that results from the corresponding movement of theslider scales. Illustrations of these functionalities are depicted anddiscussed in relation to FIGS. 13 and 14A-14C.

FIG. 11 is a block diagram 102 illustrating example data inputs andoutputs for the service and maintenance optimizing visualizationcomponent 26 depicted in FIG. 2 in accordance with an embodiment of thepresent invention. More particularly, the block diagram 102 of FIG. 11illustrates that the service and maintenance optimizing visualizationcomponent 26 is configured to utilize one or more algorithms 104 foroperating on the visualizations 88 generated from the optimizedrevenue—flexible base load visualization component 24 in order tofurnish service and maintenance visualizations 106 that offer anindication how operating conditions in the revenue transposed flexiblebase load visualizations will have on the service and maintenance of thevarious parts and components in a power plant. To this extent, operatorscan use this information to assess the impact that the operating spaceof the revenue transposed flexible base load visualizations will have onthe maintenance and service of parts of the power plant based on theoperating conditions associated with each of the operating segments. Forexample, an operator can use the service and maintenance visualizations106 to note that certain higher firing temperatures in certain marketconditions can come at price to the service and maintenance of the powerplant because such high temperatures will reduce the life cycle partsand require maintenance cost to keep running and eventual replacementcosts. As a result, the operator can refer to other operating sectionsin the service and maintenance visualizations 106 that will have lessimpact on service and maintenance, with an overall better operationalrevenue in comparison to those sections that could potentially havebetter revenue but for the effect that such corresponding values willhave on service and maintenance.

FIG. 12 is flow chart describing examples of operations performed by thealgorithm 104 associated with the service and maintenance optimizingvisualization component 26 to generate the service and maintenancevisualizations 106 depicted in FIG. 11. As shown in FIG. 12, thealgorithm 104 can begin at 108 where the optimized revenue/flexible baseload map visualizations generated by the optimized revenue/flexible baseload map visualization component 24 are obtained. Next, the impact thatthese optimized revenue/flexible base load map visualizations will haveon service and maintenance of a power plant is assessed at 110. In oneembodiment, this assessment can include performing a tradeoff analysisbetween operating conditions and their effect on services cost.

After the assessment, a visual representation can be generated at 112.In one embodiment, the visualizations can be generated by usingwell-known visualization applications that are commercially available.With the service and maintenance visualizations available, a plantoperator can use them to forecast operational scenarios, manage outagesand power plant availability in a manner that ensures that revenue ismaximized.

While, for purposes of simplicity of explanation, the operations shownin FIGS. 4, 7, 9, and 12 are described as a series of acts. It is to beunderstood and appreciated that the subject innovation associated withFIGS. 4, 7, 9, and 12 is not limited by the order of acts, as some actsmay, in accordance therewith, occur in a different order and/orconcurrently with other acts from that shown and described herein. Forexample, those skilled in the art will understand and appreciate that amethodology or operations depicted in FIGS. 4, 7, 9, and 12 couldalternatively be represented as a series of interrelated states orevents, such as in a state diagram. Moreover, not all illustrated actsmay be required to implement a methodology in accordance with theinnovation. Furthermore, interaction diagram(s) may representmethodologies, or methods, in accordance with the subject disclosurewhen disparate entities enact disparate portions of the methodologies.Further yet, two or more of the disclosed example methods can beimplemented in combination with each other, to accomplish one or morefeatures or advantages described herein.

FIG. 13 is an example showing a visualization of optimized revenuewithin a flexible base load map for variable spot market pricing inaccordance with an embodiment of the present invention. In particular,this example shows some of the aforementioned benefits of using thedispatch advisor system 18 in comparison to an approach that does nothave the capabilities of the various embodiments described herein. Inthis example of FIG. 13, the dispatch advisor system 18 is depicted asBase Load Adviser (BLA), and the non-dispatch advisor system portion isdepicted as No BLA. The market condition that is taken intoconsideration in this example is spot market power pricing. As shown inFIG. 13, the spot market power pricing is variable as it evaluatesscenarios in which the power price can include 20, 40, 60, 80, 100, and120 $/MW-hr.

With the variable power pricing, the optimal point of operation withinthe spot market condition will change. As shown in FIG. 13, the dispatchadvisor system 18 (BLA) takes into account the impact of Tfire and Tcdon combustion, the hot gas path components and rotor life includingservice expenses and maintenance factors, as well as the fuel expensesand CO₂ taxes, and thus, the impact of services on operatingexpenditures. Inclusion of service expenses and maintenance factors, aswell as the fuel expenses and CO₂ taxes, and their impact thereof,increases operational revenue, increases availability of the powerplant, and allows for outage management.

All of these considerations and their impact, which are taken intoaccount in the example of FIG. 13 for the BLA portion can providedifferent assessments and recommendations for operation in mostscenarios than that provided by the No BLA scenario. As shown in FIG.13, in the 20 $/MW-hr and 40 $/MW-hr scenarios, the BLA and the no-BLAapproaches can agree that operation of the power plant at a high outputare not recommended. However, in the 60 $/MW-hr and 80 $/MW-hrscenarios, the recommendations in the BLA and the no-BLA approaches candiffer. For example, the differing recommendations can lead to +0.55increase in revenue for the BLA approach in comparison to the no-BLAapproach, and that the revenue increase is 2% versus peak fire, due tothe BLA recommending moderate overfire (the amount of increase inTfire), as compared to the no-BLA approach. As a result of thisassessment, the BLA approach will require lower maintenance, and thus,the power plant will have higher availability in comparison to theno-BLA approach. In the 100 $/MW-hr and 120 $/MW-hr scenarios, therecommendations in the BLA and the no-BLA approaches can differ in theoperating segments that represent high to moderate overfiring. As aresult of having different assessments for some of the overfiringsegments and the Tfuel segments, the BLA approach can result in moreavailability (e.g., 1.97%) and be prepared for more outages (e.g., 2).From the scenarios depicted in FIG. 13, it is evident that when thepower plant is dispatched at required output, which is different from anoptimal operating point within the flexible base load space, the BLAapproach (i.e., the dispatch advisor system 18) can suggest a gasturbine setting at which the plant is dispatched with optimum possibleeconomics.

FIGS. 14A-14C illustrates examples how a plant operator could use thedispatch advisor system 18 depicted in FIG. 2 to manage a power plant inaccordance with various embodiments of the present invention. As shownin these examples, there are several ways that a plant operator mayutilize the dispatch advisor system 18 for on-line guidance ofoperations and for off-line planning purposes. It is understood that theexamples illustrated in FIGS. 14A-14C are merely illustrative of only afew possibilities describing how a plant operator could use the dispatchadvisor system 18 to manage the operation of a power plant and are notmeant to be limiting.

FIG. 14A depicts an example of how a plant operator could utilize thedispatch advisor system 18 for on-line guidance. As shown in FIG. 14A,the nominal base operating point 114 is Tfire=2830 F, Mn=0.796. In ascenario in which the gas turbine output exceeds the nominal baseoperating point 114, the dispatch advisor system 18 can be configured toprovide the plant operator with the guidance regarding the operation ofthe turbine. Assuming that inputs are complete and the operating revenueacross the flexible base load area has been calculated, the dispatchadvisor system 18, and interactive visualization screen like thatdepicted in FIG. 14A can be presented to the operator. The visualizationscreen of FIG. 14A, as well as the one shown in FIGS. 14B-14C, caninclude a two-dimensional array 100 showing the partitioned operatingspaces with the operational revenue assessment for each segment. Thevisualization screen can further include user interactive slider scales116 and 118. In one embodiment, the interactive slider scale 116 can beconfigured to change the firing temperature and the interactive sliderscale 118 can be configured to change the position of the inlet guidevanes in the gas turbine, and the fuel temperature of the fuel in thegas turbine. In addition, the visualization screens of FIG. 14A-14C caninclude input and output buttons 120 for receiving user input data anddisplaying output data. In one embodiment, the input and output buttons120 can be used to depict and enter values for the power plant output.With this configuration, the plant operator can control the gas turbineand the power plant output setting anywhere within the flexible baseload space depicted in the two-dimensional array 100 by moving theinteractive slider scales 116, 118 within their corresponding ranges.

FIG. 14B illustrates a scenario in which a plant operator could use avisualization screen provided by the dispatch advisor system 18 to run apower plant to a maximum revenue. In the example of FIG. 14B, the plantoperator can manually position both interactive slider scales 116 and118 to find a target point 122 with an area indicated as having the mostrevenue. This corresponds to settings for Tfire and Mn that yield thehighest operational revenue.

FIG. 14C illustrates a scenario in which a plant operator could use avisualization screen provided by the dispatch advisor system 18 to run apower plant to a defined output. In the example of FIG. 14C, the plantoperator can enable this mode by clicking on the Desired Output buttonof the input/outputs 120 displayed on the visualization screen. Theplant operator can then enter the required output (e.g., 835 MW) in theDesired Output button. When an output is entered and activated by thisoperator action, a line of constant power plant output 124 is added tothe flexible base load space depicted in the two-dimensional array 100.

At the same time, the horizontal interactive slider scale 118 can bedeactivated, and as a result, the gas turbine will be controlled bymanually setting Tfire using the interactive slider scale 116. The gasturbine IGV setting can then automatically adjust to maintain theDesired Output entered by the operator.

In order to provide a context for the various aspects of the disclosedsubject matter, FIGS. 15 and 16 as well as the following discussion areintended to provide a brief, general description of a suitableenvironment in which the various aspects of the disclosed subject mattermay be implemented.

With reference to FIG. 15, an example environment 1000 for implementingvarious aspects of the aforementioned subject matter includes a computer1012. The computer 1012 includes a processing unit 1014, a system memory1016, and a system bus 1018. The system bus 1018 couples systemcomponents including, but not limited to, the system memory 1016 to theprocessing unit 1014. The processing unit 1014 can be any of variousavailable processors. Multi-core microprocessors and othermultiprocessor architectures also can be employed as the processing unit1014.

The system bus 1018 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, 8-bit bus, IndustrialStandard Architecture (ISA), Micro-Channel Architecture (MSA), ExtendedISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Universal Serial Bus (USB),Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), and Small Computer SystemsInterface (SCSI).

The system memory 1016 includes volatile memory 1020 and nonvolatilememory 1022. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1012, such as during start-up, is stored in nonvolatile memory 1022. Byway of illustration, and not limitation, nonvolatile memory 1022 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable PROM (EEPROM), or flashmemory. Volatile memory 1020 includes random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM).

Computer 1012 also includes removable/non-removable,volatile/nonvolatile computer storage media. FIG. 15 illustrates, forexample a disk storage 1024. Disk storage 1024 includes, but is notlimited to, devices like a magnetic disk drive, floppy disk drive, tapedrive, Jaz drive, Zip drive, LS-100 drive, flash memory card, or memorystick. In addition, disk storage 1024 can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 1024 to the system bus 1018, a removableor non-removable interface is typically used such as interface 1026.

It is to be appreciated that FIG. 15 describes software that acts as anintermediary between users and the basic computer resources described insuitable operating environment 1000. Such software includes an operatingsystem 1028. Operating system 1028, which can be stored on disk storage1024, acts to control and allocate resources of the computer 1012.System applications 1030 take advantage of the management of resourcesby operating system 1028 through program modules 1032 and program data1034 stored either in system memory 1016 or on disk storage 1024. It isto be appreciated that one or more embodiments of the subject disclosurecan be implemented with various operating systems or combinations ofoperating systems.

A user enters commands or information into the computer 1012 throughinput device(s) 1036. Input devices 1036 include, but are not limitedto, a pointing device such as a mouse, trackball, stylus, touch pad,keyboard, microphone, joystick, game pad, satellite dish, scanner, TVtuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1014through the system bus 1018 via interface port(s) 1038. Interfaceport(s) 1038 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1040 usesome of the same type of ports as input device(s) 1036. Thus, forexample, a USB port may be used to provide input to computer 1012, andto output information from computer 1012 to an output device 1040.Output adapters 1042 are provided to illustrate that there are someoutput devices 1040 like monitors, speakers, and printers, among otheroutput devices 1040, which require special adapters. The output adapters1042 include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1040and the system bus 1018. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1044.

Computer 1012 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1044. The remote computer(s) 1044 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device or other common network node and the like, and typicallyincludes many or all of the elements described relative to computer1012. For purposes of brevity, only a memory storage device 1046 isillustrated with remote computer(s) 1044. Remote computer(s) 1044 islogically connected to computer 1012 through a network interface 1048and then physically connected via communication connection 1050. Networkinterface 1048 encompasses communication networks such as local-areanetworks (LAN) and wide-area networks (WAN). LAN technologies includeFiber Distributed Data Interface (FDDI), Copper Distributed DataInterface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5 and thelike. WAN technologies include, but are not limited to, point-to-pointlinks, circuit switching networks like Integrated Services DigitalNetworks (ISDN) and variations thereon, packet switching networks, andDigital Subscriber Lines (DSL).

Communication connection(s) 1050 refers to the hardware/softwareemployed to connect the network interface 1048 to the system bus 1018.While communication connection 1050 is shown for illustrative clarityinside computer 1012, it can also be external to computer 1012. Thehardware/software necessary for connection to the network interface 1048includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems and DSL modems, ISDN adapters, and Ethernet cards.

FIG. 16 is a schematic block diagram of a sample computing environment1100 with which the disclosed subject matter can interact. The samplecomputing environment 1100 includes one or more client(s) 1102. Theclient(s) 1102 can be hardware and/or software (e.g., threads,processes, computing devices). The sample computing environment 1100also includes one or more server(s) 1104. The server(s) 1104 can also behardware and/or software (e.g., threads, processes, computing devices).The servers 1104 can house threads to perform transformations byemploying one or more embodiments as described herein, for example. Onepossible communication between a client 1102 and servers 1104 can be inthe form of a data packet adapted to be transmitted between two or morecomputer processes. The sample computing environment 1100 includes acommunication framework 1106 that can be employed to facilitatecommunications between the client(s) 1102 and the server(s) 1104. Theclient(s) 1102 are operably connected to one or more client datastore(s) 1108 that can be employed to store information local to theclient(s) 1102. Similarly, the server(s) 1104 are operably connected toone or more server data store(s) 1110 that can be employed to storeinformation local to the servers 1104.

The above description of illustrated embodiments of the subjectdisclosure, including what is described in the Abstract, is not intendedto be exhaustive or to limit the disclosed embodiments to the preciseforms disclosed. While specific embodiments and examples are describedherein for illustrative purposes, various modifications are possiblethat are considered within the scope of such embodiments and examples,as those skilled in the relevant art can recognize. Therefore, sincecertain changes may be made in the above-described invention, withoutdeparting from the spirit and scope of the invention herein involved, itis intended that all of the subject matter of the above descriptionshown in the accompanying drawings shall be interpreted merely asexamples illustrating the inventive concept herein and shall not beconstrued as limiting the invention.

In this regard, while the disclosed subject matter has been described inconnection with various embodiments and corresponding figures, whereapplicable, it is to be understood that other similar embodiments can beused or modifications and additions can be made to the describedembodiments for performing the same, similar, alternative, or substitutefunction of the disclosed subject matter without deviating therefrom.Therefore, the disclosed subject matter should not be limited to anysingle embodiment described herein, but rather should be construed inbreadth and scope in accordance with the appended claims below. Forexample, references to “one embodiment” of the present invention are notintended to be interpreted as excluding the existence of additionalembodiments that also incorporate the recited features.

In the appended claims, the terms “including” and “in which” are used asthe plain-English equivalents of the respective terms “comprising” and“wherein.” Moreover, in the following claims, terms such as “first,”“second,” “third,” “upper,” “lower,” “bottom,” “top,” etc. are usedmerely as labels, and are not intended to impose numerical or positionalrequirements on their objects. The terms “substantially,” “generally,”and “about” indicate conditions within reasonably achievablemanufacturing and assembly tolerances, relative to ideal desiredconditions suitable for achieving the functional purpose of a componentor assembly. Further, the limitations of the following claims are notwritten in means-plus-function format and are not intended to beinterpreted as such, unless and until such claim limitations expresslyuse the phrase “means for” followed by a statement of function void offurther structure.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form.

What has been described above includes examples of systems and methodsillustrative of the disclosed subject matter. It is, of course, notpossible to describe every combination of components or methodologieshere. One of ordinary skill in the art may recognize that many furthercombinations and permutations of the claimed subject matter arepossible. Furthermore, to the extent that the terms “includes,” “has,”“possesses,” and the like are used in the detailed description, claims,appendices and drawings, such terms are intended to be inclusive in amanner similar to the term “comprising” as “comprising” is interpretedwhen employed as a transitional word in a claim. That is, unlessexplicitly stated to the contrary, embodiments “comprising,”“including,” or “having” an element or a plurality of elements having aparticular property may include additional such elements not having thatproperty.

This written description uses examples to disclose several embodimentsof the invention, including the best mode, and also to enable one ofordinary skill in the art to practice the embodiments of invention,including making and using any devices or systems and performing anyincorporated methods. The patentable scope of the invention is definedby the claims, and may include other examples that occur to one ofordinary skill in the art. Such other examples are intended to be withinthe scope of the claims if they have structural elements that do notdiffer from the literal language of the claims, or if they includeequivalent structural elements with insubstantial differences from theliteral languages of the claims.

Further aspects of the invention are provided by the subject matter ofthe following clauses:

A method for assisting in selecting operating conditions of a powerplant having at least one gas turbine that maximizes operationalrevenue, comprising: obtaining, by a system comprising at least oneprocessor, a flexible base load map for operating the power plant tomeet base load power demands, wherein the flexible base load mapincludes a primary base load operating space for attaining target plantpower output and efficiency, and an expanded base load portion forattaining higher plant power output and sub-optimal efficiency inrelation to the primary base load operating space, both the primary baseload operating space and the expanded base load portion including arepresentation that associates power output and efficiency values of thepower plant that result from a subset of operational parameter valuesfor operating the power plant during base load, the operationalparameters including firing temperature of the gas turbine, a positionof inlet guide vanes in the gas turbine, and fuel temperature of thefuel in the gas turbine; partitioning, by the system, the flexible baseload map into a plurality of operating segments, each operating segmentincluding a range of operating values for the operational parameters andcorresponding power output and efficiency values that are attained whileoperating the power plant at the range of operating values in theoperating segment; for each of the plurality of operating segments,determining, by the system, revenue that is generated from operating thepower plant over the range of operating values that attain thecorresponding power output and efficiency values taking intoconsideration at least one of a plurality of market conditionsassociated with a power generation market; generating, by the system, aplurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions, wherein each visualization of therevenue determined for the plurality of market conditions includes avisual representation of the revenue associated with operating the powerplant in each of the plurality of operating segments based on therespective range of operating values and power output and efficiencyvalues that are attained with the operating values; and presenting fordisplay, with the system, one or more of the plurality of visualizationsof the revenue associated with each of the operating segments in thepartitioned flexible base load map for each of the plurality of marketconditions.

The method of the preceding clause, wherein the partitioning of theflexible base load map comprises mapping the primary base load operatingspace and the expanded base load portion into a two-dimensional array.

The method of any of the preceding clauses, wherein the two-dimensionalarray comprises a first axis representative of values associated withthe firing temperature, and a second axis representative of valuesassociated with both the position of inlet guide vanes in the gasturbine, and the fuel temperature of the fuel in the gas turbine,wherein the two-dimensional array further comprises a representation ofthe efficiency values on the first axis and a representation of theoutput values on the second axis.

The method of any of the preceding clauses, wherein the determining ofrevenue of operating the power plant over each of the plurality ofoperating segments comprises ascertaining, by the system, income fromcapacity payments for power commitments entered into over a capacitymarket, and income from power sold at a spot market.

The method of any of the preceding clauses, wherein the determining ofrevenue of operating the power plant over each of the plurality ofoperating segments further comprises ascertaining expenses of operatingthe plant over each of the plurality of operating segments.

The method of any of the preceding clauses, wherein the determining ofrevenue of operating the power plant over each of the plurality ofoperating segments further comprises debiting, by the system, a sum ofthe income from the capacity payments and the income from power sold ata spot market with the expenses of operating the power plant in thesegments.

The method of any of the preceding clauses, wherein the expensescomprise one or more of fuel expenses associated with purchasing fuelfor operating the power plant, carbon taxes for emissions created fromuse of fossil fuels for power generation, and service expensesassociated with servicing and maintenance of the power plant.

The method of any of the preceding clauses, wherein the plurality ofmarket conditions comprise variable spot market power prices of powersold at a spot market, capacity payment rates for power commitmentsentered into over a capacity market, fuel expenses associated withpurchasing fuel for operating the power plant, and carbon taxes foremissions created from use of fossil fuels for power generation.

The method of any of the preceding clauses, wherein the visualrepresentation of the revenue is selected from a plurality of visualrevenue indicators, each visual revenue indicator representative of anamount of revenue that is possible from operating the power plant basedon the range of operating values and power output and efficiency valuesthat are attained with the operating values for a respective operatingsegment.

The method of any of the preceding clauses, wherein each of theplurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions are arranged as a guide in selectionof optimum operating conditions for the power plant to meet base loadpower demands at maximized revenue based on instantiations of the marketconditions.

The method of any of the preceding clauses, wherein the plurality ofvisual representations include interactive visualizations that enable apower plant operator direct manipulation and exploration ofrepresentations of data in the visualizations with respect to revenuepossibilities from operating the power plant to one more of theplurality of market conditions.

A system, comprising: a memory that stores executable components; aprocessor, operatively coupled to the memory, that executes theexecutable components, the executable components comprising: a dispatchadvisor system for assisting in selecting operating conditions of apower plant having at least one gas turbine that maximizes operationalrevenue, the dispatch advisor system configured to perform the methodcomprising: obtaining, by the processor, a flexible base load map foroperating the power plant to meet base load power demands, wherein theflexible base load map includes a primary base load operating space forattaining target plant power output and efficiency, and an expanded baseload portion for attaining higher plant power output and sub-optimalefficiency in relation to the primary base load operating space, boththe primary base load operating space and the expanded base load portionincluding a representation that associates power output and efficiencyvalues of the power plant that result from a subset of operationalparameter values for operating the power plant during base load, theoperational parameters including firing temperature of the gas turbine,a position of inlet guide vanes in the gas turbine, and fuel temperatureof the fuel in the gas turbine; partitioning, by the processor, theflexible base load map into a plurality of operating segments, eachoperating segment including a range of operating values for theoperational parameters and corresponding power output and efficiencyvalues that are attained while operating the power plant at the range ofoperating values in the operating segment; for each of the plurality ofoperating segments, determining, by the processor, revenue that isgenerated from operating the power plant over the range of operatingvalues that attain the corresponding power output and efficiency valuestaking into consideration at least one of a plurality of marketconditions associated with a power generation market; generating, by theprocessor, a plurality of visualizations of the revenue associated witheach of the operating segments in the partitioned flexible base load mapfor each of the plurality of market conditions, wherein eachvisualization of the revenue determined for the plurality of marketconditions includes a visual representation of the revenue associatedwith operating the power plant in each of the plurality of operatingsegments based on the respective range of operating values and poweroutput and efficiency values that are attained with the operatingvalues; and presenting for display, with the processor, one or more ofthe plurality of visualizations of the revenue associated with each ofthe operating segments in the partitioned flexible base load map foreach of the plurality of market conditions.

The system of the preceding clause, wherein the presenting for displayof the one or more of the plurality of visualizations of the revenueassociated with each of the operating segments in the partitionedflexible base load map for each of the plurality of market conditions,comprises appending, with the processor, one or more user interactiveslider scales configured to receive user-input for moving about each ofthe operating segments in the partitioned flexible base load map, andone or more input and output buttons for receiving user input data anddisplaying output data.

The system of any of the preceding clauses, wherein movements of each ofthe one or more user interactive slider scales controls at least one ofthe plurality of operational parameters, wherein manipulation of each ofthe one or more user interactive slider scales shows a change in revenuethat arises with an accompany change to the at least one of theplurality of operational parameters.

The system of any of the preceding clauses, wherein the one or more userinteractive slider scales comprises a first interactive slider scaleconfigured to receive changes to the firing temperature and a secondinteractive slider scale configured to receive changes to the positionof the inlet guide vanes in the gas turbine, and the fuel temperature ofthe fuel in the gas turbine.

The system of any of the preceding clauses, wherein the firstinteractive slider scale and the second interactive slider scale areconfigured for movement towards an operating segment in the partitionedflexible base load map that provides maximum revenue.

The system of any of the preceding clauses, wherein the one or moreinput and output buttons is configured to receive operating dataassociated with the operational parameters of the power plant and targetpower output and efficiency values.

The system of any of the preceding clauses, further comprisingmodifying, with the processor, the plurality of visualizations of therevenue associated with each of the operating segments in thepartitioned flexible base load map based on any data received by the oneor more input and output buttons, and presenting, with the processor, amodified visualization.

The system of any of the preceding clauses, wherein the firstinteractive slider scale and the second interactive slider scale areconfigured for movement about the modified visualization, whereinmovement of one or more of the first interactive slider scale and thesecond interactive slider scale results in a display of an output valueassociated with the power plant on the one or more input and outputbuttons that results from the corresponding movement of the sliderscales.

A non-transitory computer-readable medium having stored thereonexecutable instructions that, in response to execution, cause a systemcomprising at least one processor to perform operations directed togenerating a dispatch advisor system for assisting in selectingoperating conditions of a power plant having at least one gas turbinethat maximizes operational revenue, the operations comprising: obtaininga flexible base load map for operating the power plant to meet base loadpower demands, wherein the flexible base load map includes a primarybase load operating space for attaining target plant power output andefficiency, and an expanded base load portion for attaining higher plantpower output and sub-optimal efficiency in relation to the primary baseload operating space, both the primary base load operating space and theexpanded base load portion including a representation that associatespower output and efficiency values of the power plant that result from asubset of operational parameter values for operating the power plantduring base load, the operational parameters including firingtemperature of the gas turbine, a position of inlet guide vanes in thegas turbine, and fuel temperature of the fuel in the gas turbine;partitioning the flexible base load map into a plurality of operatingsegments, each operating segment including a range of operating valuesfor the operational parameters and corresponding power output andefficiency values that are attained while operating the power plant atthe range of operating values in the operating segment; for each of theplurality of operating segments, determining revenue that is generatedfrom operating the power plant over the range of operating values thatattain the corresponding power output and efficiency values taking intoconsideration at least one of a plurality of market conditionsassociated with a power generation market; generating a plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions, wherein each visualization of therevenue determined for the plurality of market conditions includes avisual representation of the revenue associated with operating the powerplant in each of the plurality of operating segments based on therespective range of operating values and power output and efficiencyvalues that are attained with the operating values; and presenting fordisplay one or more of the plurality of visualizations of the revenueassociated with each of the operating segments in the partitionedflexible base load map for each of the plurality of market conditions.

What is claimed is:
 1. A method for assisting in selecting operatingconditions of a power plant having at least one gas turbine thatmaximizes operational revenue, comprising: obtaining, by a systemcomprising at least one processor, a flexible base load map foroperating the power plant to meet base load power demands, wherein theflexible base load map includes a primary base load operating space forattaining target plant power output and efficiency, and an expanded baseload portion for attaining higher plant power output and sub-optimalefficiency in relation to the primary base load operating space, boththe primary base load operating space and the expanded base load portionincluding a representation that associates power output and efficiencyvalues of the power plant that result from a subset of operationalparameter values for operating the power plant during base load, theoperational parameters including firing temperature of the gas turbine,a position of inlet guide vanes in the gas turbine, and fuel temperatureof the fuel in the gas turbine; partitioning, by the system, theflexible base load map into a plurality of operating segments, eachoperating segment including a range of operating values for theoperational parameters and corresponding power output and efficiencyvalues that are attained while operating the power plant at the range ofoperating values in the operating segment; for each of the plurality ofoperating segments, determining, by the system, revenue that isgenerated from operating the power plant over the range of operatingvalues that attain the corresponding power output and efficiency valuestaking into consideration at least one of a plurality of marketconditions associated with a power generation market; generating, by thesystem, a plurality of visualizations of the revenue associated witheach of the operating segments in the partitioned flexible base load mapfor each of the plurality of market conditions, wherein eachvisualization of the revenue determined for the plurality of marketconditions includes a visual representation of the revenue associatedwith operating the power plant in each of the plurality of operatingsegments based on the respective range of operating values and poweroutput and efficiency values that are attained with the operatingvalues; and presenting for display, with the system, one or more of theplurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions.
 2. The method of claim 1, whereinthe partitioning of the flexible base load map comprises mapping theprimary base load operating space and the expanded base load portioninto a two-dimensional array.
 3. The method of claim 2, wherein thetwo-dimensional array comprises a first axis representative of valuesassociated with the firing temperature, and a second axis representativeof values associated with both the position of inlet guide vanes in thegas turbine, and the fuel temperature of the fuel in the gas turbine,wherein the two-dimensional array further comprises a representation ofthe efficiency values on the first axis and a representation of theoutput values on the second axis.
 4. The method of claim 1, wherein thedetermining of revenue of operating the power plant over each of theplurality of operating segments comprises ascertaining, by the system,income from capacity payments for power commitments entered into over acapacity market, and income from power sold at a spot market.
 5. Themethod of claim 4, wherein the determining of revenue of operating thepower plant over each of the plurality of operating segments furthercomprises ascertaining expenses of operating the plant over each of theplurality of operating segments.
 6. The method of claim 5, wherein thedetermining of revenue of operating the power plant over each of theplurality of operating segments further comprises debiting, by thesystem, a sum of the income from the capacity payments and the incomefrom power sold at a spot market with the expenses of operating thepower plant in the segments.
 7. The method of claim 5, wherein theexpenses comprise one or more of fuel expenses associated withpurchasing fuel for operating the power plant, carbon taxes foremissions created from use of fossil fuels for power generation, andservice expenses associated with servicing and maintenance of the powerplant.
 8. The method of claim 1, wherein the plurality of marketconditions comprise variable spot market power prices of power sold at aspot market, capacity payment rates for power commitments entered intoover a capacity market, fuel expenses associated with purchasing fuelfor operating the power plant, and carbon taxes for emissions createdfrom use of fossil fuels for power generation.
 9. The method of claim 1,wherein the visual representation of the revenue is selected from aplurality of visual revenue indicators, each visual revenue indicatorrepresentative of an amount of revenue that is possible from operatingthe power plant based on the range of operating values and power outputand efficiency values that are attained with the operating values for arespective operating segment.
 10. The method of claim 1, wherein each ofthe plurality of visualizations of the revenue associated with each ofthe operating segments in the partitioned flexible base load map foreach of the plurality of market conditions are arranged as a guide inselection of optimum operating conditions for the power plant to meetbase load power demands at maximized revenue based on instantiations ofthe market conditions.
 11. The method of claim 1, wherein the pluralityof visual representations include interactive visualizations that enablea power plant operator direct manipulation and exploration ofrepresentations of data in the visualizations with respect to revenuepossibilities from operating the power plant to one more of theplurality of market conditions.
 12. A system, comprising: a memory thatstores executable components; a processor, operatively coupled to thememory, that executes the executable components, the executablecomponents comprising: a dispatch advisor system for assisting inselecting operating conditions of a power plant having at least one gasturbine that maximizes operational revenue, the dispatch advisor systemconfigured to perform the method comprising: obtaining, by theprocessor, a flexible base load map for operating the power plant tomeet base load power demands, wherein the flexible base load mapincludes a primary base load operating space for attaining target plantpower output and efficiency, and an expanded base load portion forattaining higher plant power output and sub-optimal efficiency inrelation to the primary base load operating space, both the primary baseload operating space and the expanded base load portion including arepresentation that associates power output and efficiency values of thepower plant that result from a subset of operational parameter valuesfor operating the power plant during base load, the operationalparameters including firing temperature of the gas turbine, a positionof inlet guide vanes in the gas turbine, and fuel temperature of thefuel in the gas turbine; partitioning, by the processor, the flexiblebase load map into a plurality of operating segments, each operatingsegment including a range of operating values for the operationalparameters and corresponding power output and efficiency values that areattained while operating the power plant at the range of operatingvalues in the operating segment; for each of the plurality of operatingsegments, determining, by the processor, revenue that is generated fromoperating the power plant over the range of operating values that attainthe corresponding power output and efficiency values taking intoconsideration at least one of a plurality of market conditionsassociated with a power generation market; generating, by the processor,a plurality of visualizations of the revenue associated with each of theoperating segments in the partitioned flexible base load map for each ofthe plurality of market conditions, wherein each visualization of therevenue determined for the plurality of market conditions includes avisual representation of the revenue associated with operating the powerplant in each of the plurality of operating segments based on therespective range of operating values and power output and efficiencyvalues that are attained with the operating values; and presenting fordisplay, with the processor, one or more of the plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions.
 13. The system of claim 12, wherein thepresenting for display of the one or more of the plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions, comprises appending, with the processor,one or more user interactive slider scales configured to receiveuser-input for moving about each of the operating segments in thepartitioned flexible base load map, and one or more input and outputbuttons for receiving user input data and displaying output data. 14.The system of claim 13, wherein movements of each of the one or moreuser interactive slider scales controls at least one of the plurality ofoperational parameters, wherein manipulation of each of the one or moreuser interactive slider scales shows a change in revenue that ariseswith an accompany change to the at least one of the plurality ofoperational parameters.
 15. The system of claim 14, wherein the one ormore user interactive slider scales comprises a first interactive sliderscale configured to receive changes to the firing temperature and asecond interactive slider scale configured to receive changes to theposition of the inlet guide vanes in the gas turbine, and the fueltemperature of the fuel in the gas turbine.
 16. The system of claim 15,wherein the first interactive slider scale and the second interactiveslider scale are configured for movement towards an operating segment inthe partitioned flexible base load map that provides maximum revenue.17. The system of claim 15, wherein the one or more input and outputbuttons is configured to receive operating data associated with theoperational parameters of the power plant and target power output andefficiency values.
 18. The system of claim 17, further comprisingmodifying, with the processor, the plurality of visualizations of therevenue associated with each of the operating segments in thepartitioned flexible base load map based on any data received by the oneor more input and output buttons, and presenting, with the processor, amodified visualization.
 19. The system of claim 18, wherein the firstinteractive slider scale and the second interactive slider scale areconfigured for movement about the modified visualization, whereinmovement of one or more of the first interactive slider scale and thesecond interactive slider scale results in a display of an output valueassociated with the power plant on the one or more input and outputbuttons that results from the corresponding movement of the sliderscales.
 20. A non-transitory computer-readable medium having storedthereon executable instructions that, in response to execution, cause asystem comprising at least one processor to perform operations directedto generating a dispatch advisor system for assisting in selectingoperating conditions of a power plant having at least one gas turbinethat maximizes operational revenue, the operations comprising: obtaininga flexible base load map for operating the power plant to meet base loadpower demands, wherein the flexible base load map includes a primarybase load operating space for attaining target plant power output andefficiency, and an expanded base load portion for attaining higher plantpower output and sub-optimal efficiency in relation to the primary baseload operating space, both the primary base load operating space and theexpanded base load portion including a representation that associatespower output and efficiency values of the power plant that result from asubset of operational parameter values for operating the power plantduring base load, the operational parameters including firingtemperature of the gas turbine, a position of inlet guide vanes in thegas turbine, and fuel temperature of the fuel in the gas turbine;partitioning the flexible base load map into a plurality of operatingsegments, each operating segment including a range of operating valuesfor the operational parameters and corresponding power output andefficiency values that are attained while operating the power plant atthe range of operating values in the operating segment; for each of theplurality of operating segments, determining revenue that is generatedfrom operating the power plant over the range of operating values thatattain the corresponding power output and efficiency values taking intoconsideration at least one of a plurality of market conditionsassociated with a power generation market; generating a plurality ofvisualizations of the revenue associated with each of the operatingsegments in the partitioned flexible base load map for each of theplurality of market conditions, wherein each visualization of therevenue determined for the plurality of market conditions includes avisual representation of the revenue associated with operating the powerplant in each of the plurality of operating segments based on therespective range of operating values and power output and efficiencyvalues that are attained with the operating values; and presenting fordisplay one or more of the plurality of visualizations of the revenueassociated with each of the operating segments in the partitionedflexible base load map for each of the plurality of market conditions.